Comparison of Modes of Administration and Response Options in the Assessment of Subjective Health Using the First Question of SF-36

To compare two modes of administration (self-administered; by interviewer) and two response options format (using words; images of “facial-expressions”) of the first question of SF-36 (Q1SF-36), and to test its validity. We included 825 participants (20–90 years). Q1SF-36, using words or images, was included in a global questionnaire interview and at the end participants filled the SF-36. The agreement was tested by weighted kappa coefficients (WKappa). Classification Trees were used in the calibration of Q1SF-36 responses, with the physical (PDSF36) and mental dimensions of SF-36. Polyserial correlation coefficients and areas under the ROC curves (AUC) were used for validation. After categorization, using PDSF36 classification trees, the WKappa were 0.770 (self-administered vs. interviewer), 0.569 (self-administered vs. facial-expressions) and 0.566 (interviewer vs. facial-expressions). The WKappa between the PDSF36 and the modes (self-administered, interviewer and facial-expressions) were 0.784, 0.713 and 0.579 and the corresponding polyserial correlation coefficients were 0.784, 0.713 and 0.579. A good discriminatory power was found comparing the modes with the PDSF36 (AUC = 0.907, 0.923 and 0.827), but not with mental dimension (AUC = 0.538, 0.501 and 0.629). The Q1SF-36, by self-administration or interviewer, may be a valid alternative for assessment of subjective physical health, but not mental health.     

Explaining the Flight of Cupid’s Arrow: A Spatial Random Utility Model of Partner Choice

Spatial homogamy may be defined as follows: anyone may be attracted to anyone else, but near candidates are more attractive than distant candidates. In this article, we propose a model of partner choice, where homogamy is defined in terms of spatial, demographic, socioeconomic and cultural similarity. A spatial choice model using random utility theory is formulated, taking into account a relaxation of the independence from the irrelevant alternatives property, as spatial alternatives are not independent of one another. We model partner choice given the characteristics of the chosen partner and a choice set of alternatives, using unique micro data on all new cohabiters in the Netherlands, linked to other relevant data sets. The model takes the spatial locations of potential candidates within a choice set into account, including an indicator for the spatial similarity between alternatives. We find that spatial homogamy is a vital component of partner matching, aside from and adding to the spatial effects in demographic, socioeconomic and cultural homogamy. Given a choice set of partners, the highest likelihood of a match occurs with a person who is born and lives near by, who is close in age, is in the same life stage and has the same marital status, who has the same educational and income level and the same labour market status, who speaks the same dialect and lives in a culturally similar residential area. The distance effect is most pronounced for those individuals with lower levels of education and those living in rural areas.     

Combined Effects: The Influence of Organizational Form and Structural Characteristics on Contract Performance in Mixed Sector Markets

Social service contracting to nongovernmental organizations is popular form of privatization across the world. Although nonprofits are preferable social service providers for legal and normative reasons, governments in the United States increasingly rely on for-profit organizations to deliver social services. This trend warrants further exploration about whether nonprofits or for-profits perform according to theoretical expectations when they exist in the same market. This study employs qualitative comparative analysis (QCA) to examine how sector-public, nonprofit, and for-profit-combines with structural variables to produce acceptable contract performance in juvenile justice programs. QCA is a discovery-oriented research tool that determines whether combinations of variables within cases produce a specific outcome and whether those combinations are consistent across cases. I find sector is not a necessary or sufficient predictor of acceptable performance on its own. Rather it combines with market factors to lead to acceptable contract performance. Combinations vary by sector, indicating that sectors behave differently in similar circumstances. The primary theoretical contribution of this paper is to provide a nuanced account of contract performance in mixed sector markets.     

International income poverty measurement: which way now?

We critically review conceptual and empirical issues surrounding the derivation of the international poverty line, expressed in PPP-adjusted dollars and linked to various rounds of the International Comparison Program (ICP). We find that there are some limitations in the current estimation of these lines, but show that statistically superior methods lead to lines that are relatively robust and confirm the $1.25 using 2005 PPPs and suggest $1.67–1.71 using 2011 PPPs (or close to the $1.90 proposed by the World Bank if we follow the World Bank’s approach of adjusting inflation rates in some countries); they also roughly confirm the current shape of the proposed ‘weakly relative’ poverty line. Using the new absolute line based on 2011 PPPs would lead to substantially lower poverty in our estimation. The extent of the decline depends on whether and how one treats China, India, and Indonesia differently from other countries in the 2005 and 2011 PPPs. More seriously, we note that the dependence on successive ICP rounds creates conceptual and empirical problems that have become worse over time so that we suggest that it would be best to consider alternatives to the current reliance on ICP rounds and the resulting PPPs. As a short-term solution we propose to fix the international poverty line in national currencies using either the 2005 or 2011 level; in the medium term, we argue for global poverty measurement based on internationally coordinated national poverty measurement.     

How Does Women’s Decision-Making Power Affect Budget Share,Nutrition and Education in Pakistan?

Understanding the effects of power distribution, particularly women’s decision making, on human development is important. This study used a set of direct measures of decision-making power from the Pakistan Social and Living Standard Measurement Survey and examined the relationship between women’s decision-making power and the food budget share, nutrition and child schooling. It found that in Pakistan, the relationship between women’s decision-making power and nutrition was not linear and varied depending on rural or urban residence. There was no clear evidence that higher women’s decision-making power would lead to better nutrition availability in Pakistan, but overall households were more likely to consume less grain and more vegetables. When women had higher decision-making power, children, particularly rural girls, were more likely to be enrolled in school.     

Testing an Economic Model of Nonprofit Growth: Analyzing the Behaviors and Decisions of Nonprofit Organizations,Private Donors,and Governments

This study draws an economic model of the growth of nonprofit organizations by analyzing the behaviors of three major actors—nonprofit organizations, private donors, and governments—in making decisions on the allocation of limited resources for nonprofit services. Since decisions made by each actor affect resource allocation, it is important to understand what drives these decisions. The model was tested using an unbalanced, 463 panel dataset collected from 28 OECD countries over a 23-year period. The results indicated that macro- and micro-economic trends and government policies framed the decision premises of the three major actors, which led them to leverage the supply and demand for goods and services and, in turn, determined how they allocated limited resources for nonprofit services. This result implies that understanding the interdependencies of all sectors of the economy is critical to comprehending the size and development of the nonprofit sector. Effective management of micro-economic policies and macro-economic stability is necessary. More important, however, is understanding how a decision in one part of the economy will have intended and unintended effects on the nonprofit sector.     

Bayesian adjustment for unidirectional misclassification in ordinal covariates

In this paper, we study the identification of Bayesian regression models, when an ordinal covariate is subject to unidirectional misclassification. Xia and Gustafson [Bayesian regression models adjusting for unidirectional covariate misclassification. Can J Stat. 2016;44(2):198–218] obtained model identifiability for non-binary regression models, when there is a binary covariate subject to unidirectional misclassification. In the current paper, we establish the moment identifiability of regression models for misclassified ordinal covariates with more than two categories, based on forms of observable moments. Computational studies are conducted that confirm the theoretical results. We apply the method to two datasets, one from the Medical Expenditure Panel Survey (MEPS), and the other from Translational Research Investigating Underlying Disparities in Acute Myocardial infarction Patients Health Status (TRIUMPH).